Director, Marketing & Data Science

Material

$145K — $170K *
Business Services
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7–10+ years in data science, marketing analytics, or quantitative research
  • Expertise in model validation and data quality
  • Proficient in SQL and cloud data environments (Snowflake, BigQuery, AWS)
  • Bachelor's degree in a quantitative field; advanced degree preferred
  • Experience with operationalizing models in CRM or marketing platforms is a plus

Responsibilities

  • Lead AI and machine learning applications for marketing insights
  • Design and execute behavioral analytics projects
  • Integrate multiple data sources into unified analytical frameworks
  • Oversee the entire modeling lifecycle in Python or R
  • Deliver actionable insights and narratives for senior executives
  • Serve as a subject matter expert to guide clients
  • Mentor analysts and data scientists in technical and professional skills

Benefits

  • Hybrid work environment based near Los Angeles, New York City, or Austin
  • Opportunities for technical and professional growth
  • Engage in cross-disciplinary partnerships for solution building
  • Involvement in shaping analytical strategies for business development
  • Access to the latest advancements in AI and data science
Full Job Description

Director, Marketing & Data Science

This role is to be based near one of our offices in Los Angeles, New York City or Austin. (Hybrid)

About the Director, Marketing & Data Science Role

Material is seeking a Director for the Marketing & Data Science team who is passionate about using data science to solve complex marketing and customer problems. This role sits at the intersection of advanced analytics, market research, customer data, and business strategy. You will lead engagements that bring together consumer surveys, first-party CRM and CDP data, transactional data, and digital behavior to help clients make better decisions and drive measurable growth.

You lead by doing: shaping the analytical approach, guiding your team through execution, and translating model outputs into clear stories for senior, non-technical audiences. You are curious about human behavior, rigorous about methodology, and practical about how AI can accelerate the work without replacing the judgment.

What You'll Do

AI & Behavioral Analytics Leadership

  • Apply AI and machine learning — including LLMs and generative techniques — to accelerate segmentation, synthetic data generation, qualitative-to-quantitative synthesis, and automated insight generation.

  • Design and execute behavioral analytics engagements: clickstream analysis, passive behavioral data, digital journey mapping, engagement modeling, propensity and churn prediction, and customer lifetime value.

  • Integrate behavioral signals — from CRM, CDP, digital, transactional, and survey sources — into unified analytical frameworks that reflect how customers actually make decisions.

  • Lead technical execution in Python or R across the full modeling lifecycle: feature engineering, model selection, validation, interpretation, and deployment planning.

  • Stay current on advances in AI, machine learning, and behavioral science — identifying what's practically useful for clients versus what's hype.

Client & Strategic Leadership

  • Own the analytical workstream end-to-end: converting business questions into clear analytic plans, timelines, and decision-ready outputs.

  • Deliver executive-ready narratives that connect behavioral findings to marketing actions and measurable business outcomes.

  • Serve as a trusted subject matter expert — explaining complex methods, defending recommendations, and redirecting analyses that won't answer the underlying question.

  • Partner across research, strategy, technology, and data engineering to build solutions that can be activated in client environments.

  • Support business development by shaping analytical approaches, scoping work, and contributing to proposals.

Team Leadership

  • Lead and mentor a pod of analysts and data scientists — providing direction, code review, and opportunities for technical and professional growth.

  • Review analytical plans, model outputs, and client deliverables; catch risks early and help teams troubleshoot.

  • Contribute to practice growth through knowledge sharing, capability development, and methodological innovation.

Required

  • 7–10+ years in data science, marketing analytics, or quantitative research — agency, consulting, or in-house.

  • Solid grounding in model validation, data quality, and the practical tradeoffs of applying analytics to real business decisions.

  • Working knowledge of SQL and cloud data environments (Snowflake, BigQuery, AWS).

  • Bachelor's degree in statistics, data science, economics, computer science, or a related quantitative field; advanced degree preferred.

Nice to Have

  • Experience operationalizing models in CRM, CDP, or marketing automation platforms (Salesforce, HubSpot, mParticle, Braze, or similar).

  • Familiarity with passive behavioral or digital measurement data providers.

  • Experience designing agile test-and-learn programs and measuring incremental impact.

  • BI/visualization tools: Tableau, Power BI, or Looker Studio.

Pay Range: $145,000.00- 170,000.00

The range shown represents a grouping of relevant ranges currently in use at Material. Actual range for this position may differ, depending on location and specific skillset required for the work itself.

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